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Dynamic Multi-Objective Optimization With jMetal and Spark: a Case Study

dc.creatorCordero, José A.es
dc.creatorNebro, Antonio J.es
dc.creatorBarba González, Cristóbales
dc.creatorDurillo, Juan J.es
dc.creatorGarcía Nieto, José Manueles
dc.creatorNavas Delgado, Ismaeles
dc.creatorAldana Montes, José F.es
dc.date.accessioned2021-05-06T10:31:41Z
dc.date.available2021-05-06T10:31:41Z
dc.date.issued2016
dc.identifier.citationCordero, J.A., Nebro, A.J., Barba González, C., Durillo, J.J., García Nieto, J.M., Navas Delgado, I. y Aldana Montes, J.F. (2016). Dynamic Multi-Objective Optimization With jMetal and Spark: a Case Study. En MOD 2016: Second International Workshop on Machine Learning, Optimization, and Big Data (106-117), Volterra, Italy: Springer.
dc.identifier.isbn978-3-319-51468-0es
dc.identifier.issn0302-9743es
dc.identifier.urihttps://hdl.handle.net/11441/108639
dc.description.abstractTechnologies for Big Data and Data Science are receiving increasing research interest nowadays. This paper introduces the prototyping architecture of a tool aimed to solve Big Data Optimization problems. Our tool combines the jMetal framework for multi-objective optimization with Apache Spark, a technology that is gaining momentum. In particular, we make use of the streaming facilities of Spark to feed an optimization problem with data from different sources. We demonstrate the use of our tool by solving a dynamic bi-objective instance of the Traveling Salesman Problem (TSP) based on near real-time traffic data from New York City, which is updated several times per minute. Our experiment shows that both jMetal and Spark can be integrated providing a software platform to deal with dynamic multi-optimization problems.es
dc.description.sponsorshipMinisterio de Ciencia e Innovación TIN2011-25840es
dc.description.sponsorshipJunta de Andalucía P11-TIC-7529es
dc.description.sponsorshipJunta de Andalucía P12-TIC-1519es
dc.formatapplication/pdfes
dc.format.extent12es
dc.language.isoenges
dc.publisherSpringeres
dc.relation.ispartofMOD 2016: Second International Workshop on Machine Learning, Optimization, and Big Data (2016), pp. 106-117.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectMulti-objective optimizationes
dc.subjectDynamic Optimization Problemes
dc.subjectBig Data Technologieses
dc.subjectSparkes
dc.subjectStreaming Processinges
dc.subjectjMetales
dc.titleDynamic Multi-Objective Optimization With jMetal and Spark: a Case Studyes
dc.typeinfo:eu-repo/semantics/conferenceObjectes
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Ciencias de la Computación e Inteligencia Artificiales
dc.relation.projectIDTIN2011-25840es
dc.relation.projectIDP11-TIC-7529es
dc.relation.projectIDP12-TIC-1519es
dc.relation.publisherversionhttps://link.springer.com/chapter/10.1007/978-3-319-51469-7_9es
dc.identifier.doi10.1007/978-3-319-51469-7_9es
dc.publication.initialPage106es
dc.publication.endPage117es
dc.eventtitleMOD 2016: Second International Workshop on Machine Learning, Optimization, and Big Dataes
dc.eventinstitutionVolterra, Italyes
dc.relation.publicationplaceCham, Switzerlandes
dc.contributor.funderMinisterio de Ciencia e Innovación (MICIN). Españaes
dc.contributor.funderJunta de Andalucíaes

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